Afzal,, N., & Mitkov,, R. (2014). Automatic generation of multiple choice questions using dependency‐based semantic relations. Soft Computing, 18, 1269–1281.
Agarwal,, M., & Mannem,, P. (2011). Automatic gap‐fill question generation from text books. In Proceedings of the 6th workshop on innovative use of NLP for building educational applications (pp. 56–64). Stroudsburg, PA: Association for Computational Linguistics.
Bednarik,, L., & Kovacs,, L. (2012). Implementation and assessment of the automatic question generation module. In 2012 IEEE 3rd international conference on cognitive infocommunications (CogInfoCom) (pp. 687–690). IEEE.
Bhatia,, A. S., Kirti,, M., & Saha,, S. K. (2013). Automatic generation of multiple choice questions using wikipedia. In International conference on pattern recognition and machine intelligence (pp. 733–738). Springer.
Bodenreider,, O. (2004). The unified medical language system (UMLS): Integrating biomedical terminology. Nucleic Acids Research, 32, D267–D270.
Brown,, J. C., Frishkoff,, G. A., & Eskenazi,, M. (2005). Automatic question generation for vocabulary assessment. In Proceedings of the conference on human language technology and empirical methods in natural language processing (pp. 819–826). Association for Computational Linguistics.
Bunescu,, R., & Huang,, Y. (2010). Learning the relative usefulness of questions in community QA. In Proceedings of the 2010 conference on empirical methods in natural language processing, EMNLP`10 (pp. 97–107). Stroudsburg, PA: Association for Computational Linguistics. http://dl.acm.org/citation.cfm?id=1870658.1870668
Chali,, Y., & Hasan,, S. A. (2015). Towards topic‐to‐question generation. Computational Linguistics, 41, 1–20.
Collobert,, R. (2011). Deep learning for efficient discriminative parsing. In Proceedings of the fourteenth international conference on artificial intelligence and statistics (pp. 224–232).
Du,, X., Shao,, J., & Cardie,, C. (2017). Learning to ask: Neural question generation for reading comprehension. In Proceedings of the 55th annual meeting of the association for computational linguistics (Vol. 1: Long Papers, pp. 1342–1352). Vancouver, Canada: Association for Computational Linguistics. https://www.aclweb.org/anthology/P17-1123
Fattoh,, I. E., Aboutabl,, A. E., & Haggag,, M. H. (2015). Semantic question generation using artificial immunity. International Journal of Modern Education and Computer Science, 7, 1.
Graesser,, A. C., & Person,, N. K. (1994). Question asking during tutoring. American Educational Research Journal, 31, 104–137.
Heilman,, M. (2011) Automatic factual question generation from text. (Ph.D. thesis). Carnegie Mellon University.
Heilman,, M., & Smith,, N. A. (2009). Question generation via overgenerating transformations and ranking. Tech. rep., Carnegie‐Mellon Univ, Pittsburgh, PA, Language Technologies Inst.
Hussein,, H., Elmogy,, M., & Guirguis,, S. (2014). Automatic english question generation system based on template driven scheme. International Journal of Computer Science Issues (IJCSI), 11, 45.
Kalady,, S., Elikkottil,, A., & Das,, R. (2010) Natural language question generation using syntax and keywords. In Proceedings of QG2010: The third workshop on question generation (Vol. 2). questiongeneration.org.
Labutov,, I., Basu,, S., & Vanderwende,, L. (2015). Deep questions without deep understanding. In Proceedings of the 53rd annual meeting of the association for computational linguistics and the 7th international joint conference on natural language processing (Vol. 1: Long Papers, pp. 889–898).
Le,, N.‐T., Kojiri,, T., & Pinkwart,, N. (2014). Automatic question generation for educational applications – The state of art. In Advanced computational methods for knowledge engineering (pp. 325–338). New York, NY: Springer.
Liu,, M., Calvo,, R. A., & Rus,, V. (2010). Automatic question generation for literature review writing support. In International conference on intelligent tutoring systems (pp. 45–54). Springer.
Mannem,, P., Prasad,, R., & Joshi,, A. (2010). Question generation from paragraphs at upenn: Qgstec system description. In Proceedings of QG2010: The third workshop on question generation (pp. 84–91). Milton Keynes, England: The Open University.
Manning,, C. D., Surdeanu,, M., Bauer,, J., Finkel,, J., Bethard,, S. J., & McClosky,, D. (2014). The Stanford CoreNLP natural language processing toolkit. In Association for computational linguistics (ACL) system demonstrations (pp. 55–60). Stroudsburg, PA: Association for Computational Linguistics (ACL). http://www.aclweb.org/anthology/P/P14/P14-5010
Mazidi,, K., & Nielsen,, R. D. (2015). Leveraging multiple views of text for automatic question generation. In International conference on artificial intelligence in education (pp. 257–266). Springer.
McConnell,, C. C., Mannem,, P., Prasad,, R., & Joshi,, A. (2011). A new approach to ranking over‐generated questions. In 2011 AAAI fall symposium series, Palo Alto, CA: Association for the Advancement of Artificial Intelligence (AAAI).
Miller,, G. A. (1995). Wordnet: A lexical database for english. Communications of the ACM, 38, 39–41.
Mitkov,, R., Le An,, H., & Karamanis,, N. (2006). A computer‐aided environment for generating multiple‐choice test items. Natural Language Engineering, 12, 177–194.
Mostow,, J., & Chen,, W. (2009). Generating instruction automatically for the reading strategy of self‐questioning. In Artificial Intelligence in Education (pp. 465–472). Amsterdam, Holland: IOS Press.
Olney,, A. M., Graesser,, A. C., & Person,, N. K. (2012). Question generation from concept maps. Dialogue %26 Discourse, 3, 75–99.
Papasalouros,, A., Kanaris,, K., & Kotis,, K. (2008). Automatic generation of multiple choice questions from domain ontologies. In e‐Learning (pp. 427–434). Princeton, NJ: Citeseer.
Piwek,, P., & Stoyanchev,, S. (2010). Generating expository dialogue from monologue: Motivation, corpus and preliminary rules. In Human language technologies: The 2010 annual conference of the North American chapter of the association for computational linguistics (pp. 333–336). Association for Computational Linguistics.
Pradhan,, S. S., Ward,, W., & Martin,, J. H. (2008). Towards robust semantic role labeling. Computational Linguistics, 34, 289–310.
Rajpurkar,, P., Zhang,, J., Lopyrev,, K., & Liang,, P. (2016). Squad: 100,000+ questions for machine comprehension of text. arXiv preprint arXiv:1606.05250.
Ratinov,, L., & Roth,, D. (2009). Design challenges and misconceptions in named entity recognition. In Proceedings of the thirteenth conference on computational natural language learning (pp. 147–155). Association for Computational Linguistics.
Rus,, V., Cai,, Z., & Graesser,, A. (2008) Question generation: Example of a multi‐year evaluation campaign. In Proc. WS on the QGSTEC.
Scialom,, T., Piwowarski,, B., & Staiano,, J. (2019). Self‐attention architectures for answer‐agnostic neural question generation. In Proceedings of the 57th annual meeting of the Association for Computational Linguistics (pp. 6027–6032). Florence, Italy: Association for Computational Linguistics. https://www.aclweb.org/anthology/P19-1604
Song,, L., Wang,, Z., Hamza,, W., Zhang,, Y., & Gildea,, D. (2018). Leveraging context information for natural question generation. In Proceedings of the 2018 conference of the North American chapter of the association for computational linguistics: Human language technologies (Vol. 2, Short Papers, pp. 569–574). New Orleans, Louisiana: Association for Computational Linguistics. https://www.aclweb.org/anthology/N18-2090
Sumita,, E., Sugaya,, F., & Yamamoto,, S. (2005). Measuring non‐native speakers` proficiency of english by using a test with automatically‐generated fill‐in‐the‐blank questions. In Proceedings of the second workshop on building educational applications using NLP (pp. 61–68). Association for Computational Linguistics.
Tsuruoka,, Y., Tateishi,, Y., Kim,, J.‐D., Ohta,, T., McNaught,, J., Ananiadou,, S., & Tsujii,, J. (2005). Developing a robust part‐of‐speech tagger for biomedical text. In Panhellenic conference on informatics (pp. 382–392). Springer.
Varga,, A., & Ha,, L. A. (2010). Wlv: A question generation system for the qgstec 2010 task b. In Proceedings of QG2010: The third workshop on question generation (pp. 80–83). Milton Keynes, England: The Open University.
Wang,, W., Hao,, T., & Liu,, W. (2007). Automatic question generation for learning evaluation in medicine. In International conference on web‐based learning (pp. 242–251). Springer.
Zhao,, Y., Ni,, X., Ding,, Y., & Ke,, Q. (2018). Paragraph‐level neural question generation with maxout pointer and gated self‐attention networks. In Proceedings of the 2018 conference on empirical methods in natural language processing (pp. 3901–3910). Brussels, Belgium: Association for Computational Linguistics. https://www.aclweb.org/anthology/D18-1424